Resource Use and Patient Care Associated With Chronic Kidney Disease in a Managed Care Setting

OBJECTIVES: To describe the resource utilization and care of chronic kidney disease (CKD) patients in a managed care plan. METHODS: This was a retrospective claims analysis of a nationwide managed care medical and pharmacy database from September 1, 1998, to July 31, 2001. Twenty-seven health plans in 19 states distributed across the Northeast, Southeast, Midwest, and Southwest United States were represented in this analysis. CKD patients were identified using ICD-9 CM, CPT-4, and HCPCS codes indicative of dialysis. Patients continuously enrolled for at least 6 months before and 3 months after an initial dialysis event were included in the study. Health care charges and associated clinical information were assessed during 3 time periods: predialysis was from the sixth through the second month before initial dialysis, peridialysis was 30 days before and 30 days after initial dialysis, and postdialysis was the second and third month after initial dialysis. The main outcome measures were total health care charges, primary diagnoses, and diagnosis-related groups (DRGs). RESULTS: The per-patient-per-month charges were $4,265 in the predialysis period (average for 5 months), $35,292 in the peridialysis period (average for 2 months), and $15,399 in the postdialysis period (average for 2 months). The most common primary diagnosis categories during all time periods were chronic renal failure and congestive heart failure. Similarly, the most common DRGs were related to renal and heart failure. A total of 38.2% of patients did not have an initial nephrologist visit until the first dialysis event. Treatments with nutritional supplements and medications such as angiotensin-converting enzyme inhibitors and erythropoietin were found to be suboptimal. CONCLUSIONS: CKD patients generate significant medical charges during the predialysis period and after initiation of dialysis. Further investigations are warranted to assess the impact of active management of CKD patients on CKD-related health care expenditures in kidney disease.

Few economic studies have been conducted that examine the resource use associated with patient care of CKD, from predialysis through ESRD. In addition, while economic information for ESRD patients has been well documented in the United States Renal Data System (USRDS), clinical and economic information associated with predialysis CKD care has not been well documented in the current literature. Therefore, the primary aim of this study was to describe the health care resource use and patient care of CKD patients across the spectrum of disease severity, using data from a managed care setting. The rationale for these analyses is to gain a preliminary insight into the costs and patient care associated with CKD.

■■ Methods
A retrospective analysis of administrative claims was performed using a large managed care database. In 2001, enrollment in the plan was approximately 15 million average covered lives on any given day. Nearly one third (5 million) of these lives had medical claims that were adjudicated through one data processing system, and they represent the data that was the focus of this research. For proprietary reasons, this database is referred to as D1. Twenty-seven health plan sites in 19 states, distributed across the Northeast, Southeast, Midwest, and Southwest United States were represented in this analysis. The 27 sites were chosen from D1 because as a whole they had excellent completeness in terms of capturing claims and the data elements were consistent over the time period used in the analysis. The other two thirds of the initial 15 million lives had medical and pharmacy claims that were adjudicated under a separate data system (D2). Both databases (D1 and D2) contained member information such as demographic and enrollment records, medical encounter services, and charges assessed for each medical service. Although the data in D2 were available for analysis, the data were not used in this study because D1 and D2 were derived from 2 different business systems.
Patient care records outlining services the patient received while under care of the plan (i.e., hospitalizations, procedures, accompanying charges, etc.) are routinely captured. Each facility service record contains information on up to 9 diagnoses recorded with the International Classification of Diseases, Ninth Revision (ICD-9-CM) diagnosis codes and up to 6 procedures recorded with ICD-9-CM procedure codes, Current Procedural Terminology (CPT), or Health Care Financing Agency (HCFA) Common Procedure Coding System (HCPCS) codes. Medical claims and patient encounter data are collected from all health care settings operating within the plan for nearly every type of service provided to enrollees. Health plan providers submit claims either by mail or electronically. Claims submitted by medical facilities are reported via the HCFA Uniform Bill 82 (UB-82) or UB-92 form, while ambulatory claims are reported via the HCFA-1500 form. Claims for pharmacy services are submitted electronically by the pharmacy at the time prescriptions are filled. , and HCPCS codes (A4690, A4820, A4900, A4901, A4905, E1510, E1590, E1592, E1594, E1632, E1635) indicative of dialysis therapy. Patients having a procedure code for new dialysis therapy were then screened for a minimum of 9 months of continuous enrollment (minimum of 6 months preceding initial dialysis event and 3 months postdialysis) during the data analysis period. Claims prior to dialysis initiation date were evaluated to ensure that patients did not have any previous dialysis episodes. A pharmacy benefit was required for the patient' s entire enrollment period for the purpose of identifying complete medication use.

Patient Selection
A minimum time frame of 6 months predialysis and 3 months postdialysis continuous enrollment was chosen for the following reasons. A limitation of this data source was that  laboratory information was not available from the medical claims. Therefore, it is not clear from the medical claims when individual patients crossed the GFR threshold into CKD. Hence, a 6-month predialysis period was chosen to ensure, as much as possible, that patients had CKD, since the time period is closer to an actual dialysis event. If a longer interval for predialysis (i.e., 12 to 18 months) was chosen, there is a greater chance that we would have captured a time period when CKD was not present for some patients. A 3-month postdialysis period was chosen since there is high mortality associated with patients soon after the initiation of dialysis. [8][9][10][11][12][13][14][15] Thus, a shorter postdialysis analysis period was chosen in order to account for this potential occurrence. If a longer interval for postdialysis (i.e., 12 to 18 months) was chosen, there could have been many fewer patients to analyze due to death after initiation of renal replacement therapy, and characterizing resource use may have been more difficult due to the small number of patients.

Variables of Interest
The provider billing categories were ambulatory pharmacy, facility inpatient, facility noninpatient, inpatient pharmacy, physician, and allied health (medical professionals other than physicians, e.g., dentists, chiropractors, psychologists). The pri-mary variables of interest included charges according to billing category, primary diagnosis categories, and inpatient diagnosisrelated groups (DRGs). Dollars reflect submitted (not allowed) charges by the provider and therefore do not reflect managed care negotiated rates or discounts and include the member costshare. Allowed charges were not accessible for this analysis. The use of submitted charges presents a limitation since the allowed charges will generally be smaller in magnitude than the submitted charges, thereby creating less conservative estimates of cost. Secondary measurements included the quantification of clinical interventions such as nephrologist visits and claims for relevant prescription medications.

Statistical Analysis
Results from this study are descriptive in nature. Resource utilization was assessed during 3 time periods: the predialysis period was 5 months in length, from the sixth through the second month before the initial dialysis event; the peridialysis period was 2 months in length, 30 days before and 30 days after the initial dialysis event; and the postdialysis period was 2 months in length, the second and third month following the initial dialysis event. Note that for the peridialysis period, the "initial dialysis event" does not occur over an extended time frame; rather  it is 1 event occurring on 1 day. National drug code (NDC) and revenue codes were used to identify prescription usage throughout the period. Total resource utilization was expressed for each time frame as per-patient-per-month (PPPM) measures, using the differing months during each time period as the denominator. The rationale for analyzing the data in these differing time periods was to demonstrate the changes in cost and utilization surrounding the initial dialysis event. Although the time periods differ and affect the calculation of PPPM costs, it is important to evaluate patients at these times to gain insight into resource use during these 3 differing clinical periods. Using the entire 9 months as the denominator for calculating PPPM, for instance, would not yield much insight into the PPPM costs before dialysis start. All statistical programming was performed using the Statistical Analysis System statistical package, version 8.2 (SAS, Cary, NC).

■■ Results Patient Characteristics
Initially, 8,132 patients were identified as having a "first dialysis" claim, i.e., with no previous records of dialysis in the previous 6 months. Based on the inclusions of active medical and pharmacy benefits and continuous enrollment over 9 months surrounding the first dialysis, the final sample consisted of 2,114 patients. Of the 6,018 excluded patients, 181 (3.0%) had inactive medical and pharmacy benefits, while 5,837 (97.0%) had discontinuous enrollment during the 9-month period. In the final sample of 2,114 patients, 274 (13.0%) had 1 dialysis claim recorded, and 1,840 patients (87.0%) had 2 or more claims for dialysis. The mean age of the sample was 56.0 years, and 44.0% were women (Table 1). Of the 2,114 patients, 314 (14.9%) received peritoneal dialysis, 1,371 (64.8%) received hemodialysis, and 429 (20.3%) had a claim for both types. The majority of patients were middle-aged and ranged from 40 to 64 years. Patients under 21 years comprised only a small portion of the population (4.2%). Due to privacy restrictions, patient race was not recorded in the database.

Primary Diagnoses
Similar primary diagnoses were noted for the 3 analysis periods. In the predialysis stage, the most common primary diagnoses were chronic renal failure (CRF), type 2 diabetes mellitus, anemia, congestive heart failure (CHF), and hypertension. In the peridialysis period, the most common diagnoses were CRF, acute renal failure, renal failure not otherwise specified, CHF, and renal hypertension. In the postdialysis period, the most common diagnoses were CRF, renal failure not otherwise specified, CHF, anemia, and type 2 diabetes mellitus ( Table 2). Of note, CHF was the only primary diagnosis to appear consistently as a top common diagnosis in all time periods.

Resource Use-Total Charges
Resource use, total charges per month, and PPPM charges were determined for the 6 provider billing categories: facility inpatient, facility noninpatient, physician, ambulatory pharmacy, allied health, and inpatient pharmacy for the 3 analysis periods. Total charges increased over time, with a dramatic increase at the first dialysis event (Figure 2). During the predialysis period, health care charges totaled $45,076,115, with a PPPM of $4,265, and increased in the peridialysis period to $149,213,317, with a PPPM of $35,292. Total charges in the postdialysis period decreased from the peridialysis period ($65,106,179, with a PPPM of $15,399), but remained considerably higher than those in the predialysis period.
The top 5 billing categories by highest total charges in the predialysis period were facility inpatient, facility noninpatient, physician, ambulatory pharmacy, and allied health. In the subsequent study periods, the order of provider billing categories remained relatively consistent in order of magnitude (Table 3).

Facility Charges
During the predialysis period, facility inpatient hospitalization charges totaled $22,707,701, with a PPPM of $2,148, and accounted for 50.4% of overall charges, although only 25.9% of patients were hospitalized during this time. During the peridialysis and postdialysis periods, facility inpatient charges totaled $103,426,930 (PPPM $24,462) and $26,148,694 (PPPM $6,185) and accounted for 69.3% and 40.2% of overall charges, respectively (Table 3). In the peridialysis and postdialysis periods, a respective 64.4% and 28.1% of patients had hospitalizations. The percentage of patients requiring an inpatient admission more than doubled during the peridialysis relative to the predialysis period (25.9% to 64.4%, respectively).
According to inpatient DRGs, the most common reason for admission in the predialysis period was related to heart failure, with an average charge per admission of $12,172. During peridialysis, the most common reason for admission was renal failure, with an average charge per admission of $21,784. In the postdialysis period, the most common reason for admission was related to circulatory system diagnoses with complications, with an average charge per admission of $16,371 (Table 4). Of note, heart failure/shock appeared consistently as a common reason for admission in all 3 study periods. Facility noninpatient charges comprised 23.2%, 14.7%, and 39.0% of total charges during predialysis, peridialysis, and postdialysis (Table 3). Interestingly, noninpatient charges did not follow the "spiking" trend at first dialysis; rather, they increased over time (charges totaled $10,437,621, $21,937,987, and $25,377,194 during the 3 respective study periods). However, the percentage of patients utilizing noninpatient facilities remained relatively unchanged over time during the predialysis, peridyalysis, and postdialysis periods (79.7%, 90.5%, and 81.3%, respectively).

Physician Visits and Costs
In the predialysis period, total physician charges were $7,774,059, with a PPPM of $736. During the peridialysis peri-od, total physician charges were $20,079,252, with a PPPM of $4,749. During postdialysis, total physician charges were $9,494,782, with a PPPM of $2,246. While a respective 88.9%, 96.0%, and 88.0% of patients had a recorded physician visit during the 3 study periods, 38.2% did not see a nephrologist for the first time until the month during their first dialysis event (Tables 3 and 5).

Ambulatory Pharmacy
In the predialysis period, ambulatory pharmacy charges were $2,180,878, with a PPPM of $206. Ambulatory pharmacy charges during the peridialysis period were $960,754, with a PPPM of $227. During postdialysis, ambulatory pharmacy charges were $940,007, with a PPPM of $222 (Table 3). In all study periods, inpatient pharmacy charges were minimal and comprised less than 1% of total charges. The top 25 prescribed medication classes, based upon utilization as measured by the value in the "days supply" field in the pharmacy claims, were assessed for the 3 study periods (  6). Over-the-counter medications were not included. In the predialysis period, few of the expected CKD medications were among the top 25 most frequently used drugs, and only 2 different angiotensin-converting enzyme (ACE) inhibitors (11.4% of patients treated) and no phosphate binders or multivitamins/iron were listed. In the peridialysis period, only 1 type of ACE inhibitor (5.6%) and 1 type of phosphate binder (13.3%) were found among the most frequently used drugs. In the postdialysis period, 1 type of ACE inhibitor (4.5%), 2 types of phosphate binders (16.9%), and 1 type of multivitamin (8.4%) were listed. Few patients also had a recorded recombinant human erythropoietin (rHuEpo) claim in the predialysis period. The number of patients receiving rHuEpo increased every month before dialysis; during the month before first dialysis, 30.8% of patients had recorded claims for rHuEpo therapy. During postdialysis, the numbers increased slightly, ranging from 41.3% to 44.8% per month (Table 5).

■■ Discussion
Our results show that CKD patients generated significant charges to the health plan both before and after initial dialysis.
In terms of responsible payers during CKD progression, it is important to note differences in the payer mix for ESRD versus predialysis CKD.  these segments may vary depending on geographic and demographic differences across the country. As such, nationally representative numbers on the definitive payer mix in ESRD are not widely available. However, Shih 18 reported from the USRDS Dialysis Morbidity and Mortality Study data that, clearly, Medicare provides the majority of primary insurance for ESRD patients, with Medicaid and other insurance types covering a much smaller proportion of patients (Figure 3). Unlike the ESRD market, in which Medicare finances the vast majority of care, both Medicare and private payers represent a significant portion of the predialysis CKD payer mix. A recent study by Walters et al. 19 estimates the proportion of predialysis CKD patients covered by Medicare/Medicare replacement and private insurance at Gambro Healthcare to be 51.7% and 29.9%, respectively ( Figure 4). As with ESRD, Medicaid covered a small portion, in this case 14.4% of these patients. 19 The payer mix may again vary based on geographic and demographic differences across the country. Given the current state of coverage by the above parties, during the predialysis CKD period, much of the economic burden falls on the private payer, until the patient progresses into ESRD and initiates dialysis. However, even after dialysis starts, in many cases, the major shift of costs from private plan to Medicare does not occur until 33 months after the patient begins dialysis. As a result, the health plan is responsible for a CKD patient during much of their disease progression before and after dialysis.

Top 5 Inpatient Diagnosis-Related Groups
CKD patients suffer from a wide variety of comorbidities, including CHF, diabetes, and hypertension. In addition to renal disease, CHF was found to be a consistently high-frequency and high-cost primary diagnosis as well as a common cause for hospitalizations. These findings suggest that appropriate management of nonrenal conditions is an important part of patient care before dialysis.
Among the complications resulting from CKD, anemia is one of the most significant that can be addressed early in the disease progression by rHuEpo. [20][21][22][23] It is known that, if untreated, chronic anemia can lead to negative patient outcomes such as cardiovascular complications 24 and increased morbidity and mortality. However, recent investigations of the Medicare ESRD population have shown that an increasing hematocrit level is associated with decreased risks of hospitalizations and mortality. Xia et al. 15 found that compared to patients with a hematocrit of 30% to <33%, patients with a hematocrit level below 30% had a statistically significant 7% to 18% increased risk of hospitalization, while patients with a hematocrit level of 33% to <36% had a significant 7% decreased risk. In a similar study, Ma et al. 25 found that compared to a patients with a hematocrit of 30% to <33%, patients with a hematocrit level below 30% had a statistically significant 12% to 33% increased risk of mortality, while patients with a hematocrit level of 33% to <36% had a significant 4% decreased risk.
The number of patients in this analysis with a claim for rHuEpo was minimal, both before and after dialysis. The num-ber of patients on rHuEpo is considered "low" when compared to literature assessing the prevalence of anemic patients beginning dialysis. An analysis by Obrador 11 of 155,076 patients starting hemodialysis in the United States found that 67% of patients had a hematocrit less than 30% and 51% had a hematocrit less than 28%. This is in contrast to the 2000 NKF-K/DOQI guidelines, which recommend a target hematocrit of 33% to 36% in CKD patients. 26 However, overall, only 23% received rHuEpo therapy before ESRD. These results are somewhat similar to our findings, where 30.8% of patients had a claim for rHuEpo in the month prior to dialysis.
In another study in a sample of 602 predialysis patients, a hematocrit of <30% was present in 38% of patients, and 59% of these patients received rHuEpo. 7 No laboratory data were available in the claims database for our analysis. However, if the figure that 67% of patients starting dialysis have a hematocrit below 30% is representative, then the number of patients treated with rHuEpo both predialysis and postdialysis in our analysis is suboptimal. It is possible that the charge for rHuEpo was included in a physician visit and was not captured in the database. Since the rHuEpo use was captured via specific NDC codes, HCPCS Q-codes, and revenue codes, rHuEpo within a claim for a doctor visit would not have been recorded and captured. However, from the available literature it seems that treatment of anemia occurring before dialysis initiation may be not be addressed properly.
In addition to the low rHuEpo claims during predialysis, lisinopril and quinapril were the only ACE inhibitors reported in the claims for top 25 medications. Only 11.4% of patients were on either medication, although 34.8% of patients had a diagnosis for diabetes during predialysis. Similarly in the peridialysis and postdialysis periods, only 5.6% and 4.5% of patients had a claim for lisinopril, which was the only ACE inhibitor listed in the top 25 for these time periods. During these time periods, 35.1% and 30.3% of patients were diabetic, respectively, suggesting suboptimal use of ACE inhibitors in the diabetic population. Lewis 27  demonstrated that the ACE inhibitor captopril protected against deterioration in renal function in type 1 diabetic nephropathy and was significantly more effective than blood-pressure control alone. The treatment of diabetic predialysis CKD patients with ACE inhibitors produced a 67% reduction in relative risk of kidney disease progression. In addition, ACE inhibitors are still the medication of choice for patients with type 1 diabetes and nephropathy. ACE inhibitors or angiotensin receptor blockers should be considered first-line therapy for patients with type 2 diabetes and nephropathy. 28 The presence of claims for phosphate binders and multivitamins also did not appear in the top 25 drugs until the peridialysis and postdialysis periods. Control of parathyroid hormone (PTH) and calcium-phosphorus product may play an important role in the management of renal disease patients, especially in the maintenance of bone health and vascular calcification. By dialysis initiation, most patients have some form of secondary hyperparathyroidism characterized by elevated PTH, calcium, and phosphorus levels. Such alterations in these biochemical parameters can lead to cardiac and vascular calcification, parathyroid gland hyper-plasia, and osteomalacia. [29][30][31][32] As such, this is an area that needs to be addressed by providers in the early stages of renal disease.

First Nephrologist Visits and rHuEpo Claims
Although patients may have been receiving inadequate medications during the predialysis CKD period, the study sample sought care before dialysis initiation, with 87.4% of all patients having at least one recorded physician visit. Before starting dialysis, 76.5% of patients had utilized outpatient (76.5%) and inpatient (25.5%) services. However, almost 40% did not have a first nephrologist visit until their first dialysis session. Published literature suggests that earlier identification and focused management of predialysis CKD patients as well as early referral to a nephrologist may improve patient outcomes after the start of dialysis. [4][5][6][7][8][9][10][11][12][13][14][15][16] While this study only describes current trends with respect to timing of nephrologist referrals and appropriate medication use, further studies are warranted to clarify the impacts of such interventions.

■■ Limitations
As noted earlier, a limitation of this study is that laboratory values were unavailable in the claims database. Since the selection  of patients was not based on GFR levels, the time point during the predialysis period at which patients crossed the threshold for CKD is not known. However, given the limited 6-month time frame before dialysis and the presence of dialysis itself, it is likely that patients had progressive kidney disease. No hemoglobin or hematocrit laboratory data were available, so it is not known how many patients were considered to be anemic. A second limitation is that submitted charges were used in the analysis and not allowed charges. Net health plan costs may be lower, particularly after provider discounts and after subtraction of member cost-share responsibility from allowed charges. These submitted charges may overstate the actual financial burden for the managed care plan. Third, while we could measure claims for medications, we could not assess the impact of these medications on patient outcomes such as mortality, hospitalizations, and delay of disease progression.
Such impacts may only be demonstrated through a clinical trial or disease management program. Fourth, it is unclear how much of the charges were billed to Medicare before and after the start of dialysis. However, since most patients 65 years and above would have Medicare as a primary payer before and after dialysis start and those below 65 years would not have Medicare as a primary payer until 33 months after dialysis start, Medicare charges may not have had a great effect on the charge totals. Finally, the strict inclusion of 9 months of continuous enrollment may have excluded other CKD patients from the analysis. As such, the costs incurred by all CKD patients covered in the health plans were not captured due to these patient exclusions. Interestingly, considering that only 2,114 patients from 27 health plans generated such significant charges in this study, one need only consider the number of CKD patients estimated in NHANES III to comprehend the magnitude of financial burden to other health plans across the country.

■■ Conclusion
The results of this study showed increasing costs as CKD patients approached dialysis, with a considerably high average submitted charge PPPM. In addition, the data suggest that patients may not be seeing nephrologists early in their disease progression or receiving the expected medications before initiation of dialysis. Additional research is warranted to determine if increased patient monitoring and physician education about the importance of predialysis care have the potential to decrease resource utilization. In addition, opportunities exist to improve patient care in predialysis through close management of anemia, administration of appropriate medications and nutritional supplements, and better management of comorbid conditions. Our results may be of interest to health care payers and providers to use as a basis for future studies to assess the impact of active interventions in CKD or as a baseline to assess the impact of future changes in nephrology practice.  Walters et al., 2000. 19